[
https://issues.apache.org/jira/browse/FLINK-2157?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Theodore Vasiloudis updated FLINK-2157:
---------------------------------------
Fix Version/s: 0.10
> Create evaluation framework for ML library
> ------------------------------------------
>
> Key: FLINK-2157
> URL: https://issues.apache.org/jira/browse/FLINK-2157
> Project: Flink
> Issue Type: New Feature
> Components: Machine Learning Library
> Reporter: Till Rohrmann
> Labels: ML
> Fix For: 0.10
>
>
> Currently, FlinkML lacks means to evaluate the performance of trained models.
> It would be great to add some {{Evaluators}} which can calculate some score
> based on the information about true and predicted labels. This could also be
> used for the cross validation to choose the right hyper parameters.
> Possible scores could be F score [1], zero-one-loss score, etc.
> Resources
> [1] [http://en.wikipedia.org/wiki/F1_score]
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
